{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2cd1fccc-c948-4245-89d2-aa15fa7cb6e0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "葡萄酒数据集如下:\n",
      "     label     a1    a2    a3    a4   a5    a6    a7    a8    a9    a10   a11  \\\n",
      "0        1  14.23  1.71  2.43  15.6  127  2.80  3.06  0.28  2.29   5.64  1.04   \n",
      "1        1  13.20  1.78  2.14  11.2  100  2.65  2.76  0.26  1.28   4.38  1.05   \n",
      "2        1  13.16  2.36  2.67  18.6  101  2.80  3.24  0.30  2.81   5.68  1.03   \n",
      "3        1  14.37  1.95  2.50  16.8  113  3.85  3.49  0.24  2.18   7.80  0.86   \n",
      "4        1  13.24  2.59  2.87  21.0  118  2.80  2.69  0.39  1.82   4.32  1.04   \n",
      "..     ...    ...   ...   ...   ...  ...   ...   ...   ...   ...    ...   ...   \n",
      "173      3  13.71  5.65  2.45  20.5   95  1.68  0.61  0.52  1.06   7.70  0.64   \n",
      "174      3  13.40  3.91  2.48  23.0  102  1.80  0.75  0.43  1.41   7.30  0.70   \n",
      "175      3  13.27  4.28  2.26  20.0  120  1.59  0.69  0.43  1.35  10.20  0.59   \n",
      "176      3  13.17  2.59  2.37  20.0  120  1.65  0.68  0.53  1.46   9.30  0.60   \n",
      "177      3  14.13  4.10  2.74  24.5   96  2.05  0.76  0.56  1.35   9.20  0.61   \n",
      "\n",
      "      a12   a13  \n",
      "0    3.92  1065  \n",
      "1    3.40  1050  \n",
      "2    3.17  1185  \n",
      "3    3.45  1480  \n",
      "4    2.93   735  \n",
      "..    ...   ...  \n",
      "173  1.74   740  \n",
      "174  1.56   750  \n",
      "175  1.56   835  \n",
      "176  1.62   840  \n",
      "177  1.60   560  \n",
      "\n",
      "[178 rows x 14 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "names=['label','a1','a2','a3','a4','a5','a6','a7','a8','a9','a10','a11','a12','a13']\n",
    "dataset=pd.read_csv(\"wine.data\",names=names)\n",
    "print(\"葡萄酒数据集如下:\")\n",
    "print(dataset)\n",
    "data=dataset.iloc[range(0,178),range(1,14)]\n",
    "target=dataset.iloc[range(0,178),range(0,1)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "00ca30d5-5116-43e9-9e0f-bcbd4e75cb0b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a 1 中异常值: []\n",
      "a 2 中异常值: [5.8 5.51 5.65]\n",
      "a 3 中异常值: [1.36 3.22 3.23]\n",
      "a 4 中异常值: [10.6 30.0 28.5 28.5]\n",
      "a 5 中异常值: [151.0 139.0 136.0 162.0]\n",
      "a 6 中异常值: []\n",
      "a 7 中异常值: []\n",
      "a 8 中异常值: []\n",
      "a 9 中异常值: [3.28 3.58]\n",
      "a 10 中异常值: [10.8 13.0 11.75 10.68]\n",
      "a 11 中异常值: [1.71]\n",
      "a 12 中异常值: []\n",
      "a 13 中异常值: []\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 15 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style(style='darkgrid')\n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "data.plot(kind='box',subplots=True,layout=(3,5),sharex=False,sharey=False)\n",
    "p=data.boxplot(return_type='dict')\n",
    "for i in range(13):\n",
    "    y=p['fliers'][i].get_ydata()\n",
    "    print('a',i+1,'中异常值:',y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0c5f1ff8-78bf-422d-9ebc-880acc2f26f3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:base] *",
   "language": "python",
   "name": "conda-base-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
